Download or read book Implied Binomial Trees with Cubic Spline Smoothing written by Yisong S. Tian and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Implied binomial trees are typically constructed by fitting a risk-neutral density (in the form of ending nodal probabilities) to observed option prices (e.g., Rubinstein [1994]). This commonly used approach requires the solution of a high dimensional quadratic program with the number of unknowns proportional to the number of binomial periods. In this paper, we propose a more efficient implementation of implied binomial trees by incorporating cubic spline smoothing in the quadratic program. Only a selected subset of ending nodal probabilities is treated as unknowns while the remainder is interpolated using cubic splines. The reduction in dimensionality of the quadratic program can substantially improve the efficiency of implied binomial trees without any loss in numerical accuracy. More importantly, our smoothing method can overcome the overfitting problem in the implied binomial tree scheme and minimize distortions to the extracted risk-neutral density even when option prices are observed with error.